AI-Powered Tools in English Language Education: Opportunities, Limitations, and Ethical Concerns
DOI:
https://doi.org/10.67313/slijms.2026.73Keywords:
Artificial Intelligence, English Language Education, Generative AI, English Language Teaching, Digital Pedagogy, Personalized Learning, Academic Integrity, Algorithmic Bias, Educational Ethics, Learner Autonomy.Abstract
The increasing integration of Artificial Intelligence (AI) into English language education has introduced significant changes in teaching methodologies, learner engagement, assessment practices, and the development of linguistic competencies. AI-powered tools, including intelligent tutoring systems, generative language models, automated writing evaluation platforms, adaptive learning applications, speech-recognition technologies, and conversational agents, are creating opportunities for personalized instruction, immediate feedback, autonomous learning, and interactive language practice. However, their educational benefits are accompanied by substantial limitations and ethical concerns involving algorithmic bias, inaccurate linguistic feedback, data privacy, academic dishonesty, digital inequality, cultural representation, and excessive technological dependence. This study critically examines the opportunities, limitations, and ethical implications of AI-powered tools in English language education through a qualitative, literature-based analytical approach. Drawing upon contemporary scholarship, including research published in the Stanzaleaf International Journal of Multidisciplinary Studies, the paper explores how technological assistance can support linguistic development without compromising creativity, critical thinking, learner independence, or the responsibilities of educators. The study proposes a Human-Centred Ethical AI Integration Framework that integrates pedagogical relevance, learner autonomy, teacher mediation, digital equity, and ethical accountability. The analysis suggests that AI-assisted English language education is most defensible when technological systems enhance rather than replace human interaction, contextual understanding, and independent language production. The paper concludes that the sustainable integration of AI requires comprehensive digital literacy, transparent institutional policies, professional development, and learner-centred pedagogical practices.
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